Many industries use repairable, or “rotable,” inventories for economic reasons. Rotable parts are different from “expendable” parts, which are parts having a low enough value that the repair of such parts does not make economic sense. Rather, such expendible parts are merely discarded and replaced with new parts. Rotable parts, by contrast, tend to be more expensive, making their repair and reinstallation, rather than simple replacement with a new part, more economically justifiable.
Repairing a part or getting a new replacement can have uncertain lead times (i.e., the time interval between ordering a replacement and its delivery), and therefore rotable part inventories are used to bridge the gap between demand for the part and its supply as well as to maintain a selected high level of customer service. Due to the high cost of rotable parts, however, it is desirable to minimize the number of rotable parts held in inventory. But balancing minimal inventory with a desired customer service level (i.e., a measure of customer service defined as a ratio of parts delivered on time to the number of parts ordered) is difficult because the lead times for repairing parts and obtaining replacements are uncertain. Thus, there is a desire to calculate a minimum rotable inventory level that can satisfy a given customer service level.
Currently-known attempts to create models solving this problem have not provided satisfactory solutions because they use deterministic methods that assume parts arrive into a repair shop and are repaired according to standard time distributions. In actual practice, however, arrivals and repair time are much more uncertain. Thus, current models for optimizing rotable inventory do not generate satisfactory solutions because they fail to take these uncertainties into account. Further, assets may contain multiple types of rotable parts and the asset service level is determined by the service levels of individual part types. The interrelationships between those part types make it more difficult to determine optimal inventory levels for individual part types to achieve a desired assert service level. Deterministic methods are unable to consider the interrelationships between the parts.
There is a desire for a method that can calculate the optimum amount of rotable inventory needed to satisfy a given customer service level while taking these uncertainties into account.